Loyalty, shopping preferences, customer life cycle management, and transactions

Reward is a big data company. Every year, we track a few billion transactions worth billions of pounds (obviously, in an anonimised and secure way, respecting all industry standards and security policies and regulations).

We introduced card linked offers a few years ago, and since then we use massive amounts of data to identify the best prospects for a retailer, and offer them discounts on their custom, to help them acquire new customers, retain their existing ones, or turn lukewarm ones into great customers. And of course, to offer better conditions and opportunities to save to millions of shoppers.

The technology is quite disruptive in the marketing space, be it online or off-line, yet very simple and seamless for retailers and customers. We take the complexity into our platform and processes to leave only the fun (and rewarding) part to our customers. There is no integration and no staff training on the retailer side, and no plastic cards on the consumer side.

We have made loyalty cards un-necessary, and have taken performance marketing a couple of notches up (if not more). Once a consumer has registered his payment card (any payment card) with any of our publishers, we start tracking, with his explicit permission, his spending behaviour (on-line and off-line) and, with lots of other data-points, we identify the best offers for him/her. The publisher presents the offers to the consumer, and the next time the consumer shops and swipes the card, we intercept the transaction and voilà, cash is credited back into his account.

Tracking millions of cards we have a pretty accurate picture of what’s going on in UK: at customer level, at retailer level, at national or local level. To our transactional data we overlay other kinds of information, such as location, proximity, demographic, behavioural, to understand what it takes to shift a consumer’s brand preference and reward him/her for that change.

Differently from similar offers (there aren’t many, you could count them on the fingers of one of your hands in the whole world, but they do exist), we do not do advertising. We provide customer life cycle management, and change customer shopping preferences, by managing each customer in a personalised way according to what stage of the funnel he is at. If you have ever thought to genuine, real 1to1 marketing, then you thought to us.

We are totally data driven, and we can afford to be. Every day we run control/treatment tests and analysis to inform our platform decisions. Our sales forecasts are based on models that take into considerations spend behaviours of millions of people, and performance metrics of thousands of campaigns.

And if you were wondering how my job is informed by data at Reward, well, here are some snippets:

Every Monday morning I receive a sales tracker with weekly forecast 12 weeks into the future, with a few dozen metrics
Every Monday morning I receive schedules for all our teams which stretch 4 weeks into the future
Every day, including Saturdays and Sundays, I receive up to date metrics on revenues, retailers spend, customer spend, transactions, and trends 3 years back, at aggregated and publisher level
And a few more data-points every day
Our offers are communicated on a 1 to 1 basis. Our systems calculate propensity, relevancy, benefit to customers and retailers, and monetisation potential and choose the best offers to provide each and every single customer. The results are gathered, filtered, aggregated, compared to control sets, analysed and re-aggregated for retailers consumption, so to enable them to understand the real profitability of the activities, and at a different level of aggregation for our data scientist and algorithms to understand how our platform can improve, in order to provide better returns to retailers, and better opportunities to consumers, every minute of the day.

What we are doing is changing customer shopping preferences in a world of constrained customer attention, and in the most profitable way for all the stakeholders. Our platform does this a few million times every month, influencing a few hundreds million pounds of consumer spend every month, delivering significant incremental profits to our retailers, and millions of pounds in savings and rewards to their customers.

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